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arXiv · 0904.0106

Robust estimation for ARMA models

Nora Muler·Daniel Peña·Víctor J. Yohai
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Abstract

This paper introduces a new class of robust estimates for ARMA models. They are M-estimates, but the residuals are computed so the effect of one outlier is limited to the period where it occurs. These estimates are closely related to those based on a robust filter, but they have two important advantages: they are consistent and the asymptotic theory is tractable. We perform a Monte Carlo where we show that these estimates compare favorably with respect to standard M-estimates and to estimates based on a diagnostic procedure.

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Nora Muler, Daniel Peña, Víctor J. Yohai. 2009-04-01. Robust estimation for ARMA models. https://doi.org/10.1214/07-aos570

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